Multiparametric Magnetic Resonance Imaging in the follow-up of non-muscle-invasive bladder tumors after intravesical instillations: a promising tool.

PURPOSE: The standard follow-up for non-muscle-invasive bladder cancer is based on cystoscopy. Unfortunately, post-instillation inflammatory changes can make the interpretation of this exam difficult, with lower specificity. This study aimed to evaluate the interest of bladder MRI in the follow-up of patients following intravesical instillation. METHODS: Data from patients who underwent cystoscopy and bladder MRI in a post-intravesical instillation setting between February 2020 and March 2023 were retrospectively collected. Primary endpoint was to evaluate and compare the diagnostic performance of cystoscopy and bladder MRI in the overall cohort (n = 67) using the pathologic results of TURB as a reference. The secondary endpoint was to analyze the diagnostic accuracy of cystoscopy and bladder MRI according to the appearance of the lesion on cystoscopy [flat (n = 40) or papillary (n = 27)]. RESULTS: The diagnostic performance of bladder MRI was better than that of cystoscopy, with a specificity of 47% (vs. 6%, p < 0.001), a negative predictive value of 88% (vs. 40%, p = 0.03), and a positive predictive value of 66% (vs. 51%, p < 0.001), whereas the sensitivity did not significantly differ between the two exams. In patients with doubtful cystoscopy and negative MRI findings, inflammatory changes were found on TURB in most cases (17/19). The superiority in MRI bladder performance prevailed for "flat lesions", while no significant difference was found for "papillary lesions". CONCLUSIONS: In cases of doubtful cystoscopy after intravesical instillations, MRI appears to be relevant with good performance in differentiating post-therapeutic inflammatory changes from recurrent tumor lesions and could potentially allow avoiding unnecessary TURB.

Takotsubo Syndrome and Coronary Artery Disease: Which Came First-The Chicken or the Egg?

Takotsubo syndrome (TTS) is a clinical condition characterized by temporary regional wall motion anomalies and dysfunction that extend beyond a single epicardial vascular distribution. Various pathophysiological mechanisms, including inflammation, microvascular dysfunction, direct catecholamine toxicity, metabolic changes, sympathetic overdrive-mediated multi-vessel epicardial spasms, and transitory ischemia may cause the observed reversible myocardial stunning. Despite the fact that TTS usually has an acute coronary syndrome-like pattern of presentation, the absence of culprit atherosclerotic coronary artery disease is often reported at coronary angiography. However, the idea that coronary artery disease (CAD) and TTS conditions are mutually exclusive has been cast into doubt by numerous recent studies suggesting that CAD may coexist in many TTS patients, with significant clinical and prognostic repercussions. Whether the relationship between CAD and TTS is a mere coincidence or a bidirectional cause-and-effect is still up for debate, and misdiagnosis of the two disorders could lead to improper patient treatment with unfavourable outcomes. Therefore, this review seeks to provide a profound understanding of the relationship between CAD and TTS by analyzing potential common underlying pathways, addressing challenges in differential diagnosis, and discussing medical and procedural techniques to treat these conditions appropriately.

Association of digital measures and self-reported fatigue: a remote observational study in healthy participants and participants with chronic inflammatory rheumatic disease.

Background: Fatigue is a subjective, complex and multi-faceted phenomenon, commonly experienced as tiredness. However, pathological fatigue is a major debilitating symptom associated with overwhelming feelings of physical and mental exhaustion. It is a well-recognized manifestation in chronic inflammatory rheumatic diseases, such as Sjögren's Syndrome and Systemic Lupus Erythematosus and an important predictor of patient's health-related quality of life (HRQoL). Patient reported outcome questions are the key instruments to assess fatigue. To date, there is no consensus about reliable quantitative assessments of fatigue. Method: Observational data for a period of one month were collected from 296 participants in the United States. Data comprised continuous multimodal digital data from Fitbit, including heart rate, physical activity and sleep features, and app-based daily and weekly questions covering various HRQoL factors including pain, mood, general physical activity and fatigue. Descriptive statistics and hierarchical clustering of digital data were used to describe behavioural phenotypes. Gradient boosting classifiers were trained to classify participant-reported weekly fatigue and daily tiredness from multi-sensor and other participant-reported data, and extract a set of key predictive features. Results: Cluster analysis of Fitbit parameters highlighted multiple digital phenotypes, including sleep-affected, fatigued and healthy phenotypes. Features from participant-reported data and Fitbit data both contributed as key predictive features of weekly physical and mental fatigue and daily tiredness. Participant answers to pain and depressed mood-related daily questions contributed the most as top features for predicting physical and mental fatigue, respectively. To classify daily tiredness, participant answers to questions on pain, mood and ability to perform daily activities contributed the most. Features related to daily resting heart rate and step counts and bouts were overall the most important Fitbit features for the classification models. Conclusion: These results demonstrate that multimodal digital data can be used to quantitatively and more frequently augment pathological and non-pathological participant-reported fatigue.

Mazabraud Syndrome Associated with McCune-Albright Syndrome: A Case Report and Literature Review.

The Mazabraud syndrome is a rare form of bone fibrous dysplasia associated with intramuscular myxomas. The McCune-Albright syndrome is characterized by the association of dysplasia fibrous bone to one or more extra-osseous manifestations, including café-au-lait skin spots and endocrine disturbances. Here, we report on a new case of a 52-year-old man with sacroiliac polyostotic bone fibrous dysplasia associated with intramuscular myxomas of the left buttock and thigh and a café-au-lait skin spot. Biopsy analysis of one muscular lesion on the left thigh analysis revealed a spindle cell tumor with myxoid stroma with GNAS gene mutation, confirming the diagnosis of intramuscular myxoma. Given the absence of radiological sign of malignancy at the bone level and a few pains relieved by simple analgesics, no specific treatment was applied. In March 2022, after 18 months of follow-up, the magnetic resonance imaging and the PET-CT scan showed a stable disease. To our knowledge, this case is the fourth one reporting association of Mazabraud syndrome and McCune-Albright syndrome in a man. The association of intramuscular tumors and bone tumors in the same anatomical region and without any continuity, especially in lower limbs, must evoke the diagnosis of Mazabraud syndrome.

Functional Mitral and Tricuspid Regurgitation across the Whole Spectrum of Left Ventricular Ejection Fraction: Recognizing the Elephant in the Room of Heart Failure.

Functional mitral regurgitation (FMR) and tricuspid regurgitation (FTR) occur due to cardiac remodeling in the presence of structurally normal valve apparatus. Two main mechanisms are involved, distinguishing an atrial functional form (when annulus dilatation is predominant) and a ventricular form (when ventricular remodeling and dysfunction predominate). Both affect the prognosis of patients with heart failure (HF) across the entire spectrum of left ventricle ejection fraction (LVEF), including preserved (HFpEF), mildly reduced (HFmrEF), or reduced (HFrEF). Currently, data on the management of functional valve regurgitation in the various HF phenotypes are limited. This review summarizes the epidemiology, pathophysiology, and treatment of FMR and FTR within the different patterns of HF, as defined by LVEF.

Measuring Health-Related Quality of Life With Multimodal Data: Viewpoint.

The ability to objectively measure aspects of performance and behavior is a fundamental pillar of digital health, enabling digital wellness products, decentralized trial concepts, evidence generation, digital therapeutics, and more. Emerging multimodal technologies capable of measuring several modalities simultaneously and efforts to integrate inputs across several sources are further expanding the limits of what digital measures can assess. Experts from the field of digital health were convened as part of a multi-stakeholder workshop to examine the progress of multimodal digital measures in two key areas: detection of disease and the measurement of meaningful aspects of health relevant to the quality of life. Here we present a meeting report, summarizing key discussion points, relevant literature, and finally a vision for the immediate future, including how multimodal measures can provide value to stakeholders across drug development and care delivery, as well as three key areas where headway will need to be made if we are to continue to build on the encouraging progress so far: collaboration and data sharing, removal of barriers to data integration, and alignment around robust modular evaluation of new measurement capabilities.

Translational precision medicine: an industry perspective.

In the era of precision medicine, digital technologies and artificial intelligence, drug discovery and development face unprecedented opportunities for product and business model innovation, fundamentally changing the traditional approach of how drugs are discovered, developed and marketed. Critical to this transformation is the adoption of new technologies in the drug development process, catalyzing the transition from serendipity-driven to data-driven medicine. This paradigm shift comes with a need for both translation and precision, leading to a modern Translational Precision Medicine approach to drug discovery and development. Key components of Translational Precision Medicine are multi-omics profiling, digital biomarkers, model-based data integration, artificial intelligence, biomarker-guided trial designs and patient-centric companion diagnostics. In this review, we summarize and critically discuss the potential and challenges of Translational Precision Medicine from a cross-industry perspective.

A Study of Novel Exploratory Tools, Digital Technologies, and Central Nervous System Biomarkers to Characterize Unipolar Depression.

Background: Digital technologies have the potential to provide objective and precise tools to detect depression-related symptoms. Deployment of digital technologies in clinical research can enable collection of large volumes of clinically relevant data that may not be captured using conventional psychometric questionnaires and patient-reported outcomes. Rigorous methodology studies to develop novel digital endpoints in depression are warranted. Objective: We conducted an exploratory, cross-sectional study to evaluate several digital technologies in subjects with major depressive disorder (MDD) and persistent depressive disorder (PDD), and healthy controls. The study aimed at assessing utility and accuracy of the digital technologies as potential diagnostic tools for unipolar depression, as well as correlating digital biomarkers to clinically validated psychometric questionnaires in depression. Methods: A cross-sectional, non-interventional study of 20 participants with unipolar depression (MDD and PDD/dysthymia) and 20 healthy controls was conducted at the Centre for Human Drug Research (CHDR), the Netherlands. Eligible participants attended three in-clinic visits (days 1, 7, and 14), at which they underwent a series of assessments, including conventional clinical psychometric questionnaires and digital technologies. Between the visits, there was at-home collection of data through mobile applications. In all, seven digital technologies were evaluated in this study. Three technologies were administered via mobile applications: an interactive tool for the self-assessment of mood, and a cognitive test; a passive behavioral monitor to assess social interactions and global mobility; and a platform to perform voice recordings and obtain vocal biomarkers. Four technologies were evaluated in the clinic: a neuropsychological test battery; an eye motor tracking system; a standard high-density electroencephalogram (EEG)-based technology to analyze the brain network activity during cognitive testing; and a task quantifying bias in emotion perception. Results: Our data analysis was organized by technology - to better understand individual features of various technologies. In many cases, we obtained simple, parsimonious models that have reasonably high diagnostic accuracy and potential to predict standard clinical outcome in depression. Conclusion: This study generated many useful insights for future methodology studies of digital technologies and proof-of-concept clinical trials in depression and possibly other indications.

COVID-19 and breast fine needle aspiration cytology method: What should we change?

INTRODUCTION: Air-dried slide preparation for fine needle aspiration cytology procedures is currently considered unsafe because of the risk of infectious aerosols of coronavirus 19. This study compares the safety and accuracy of two different protocols, one with and one without air-dried slides. METHODS: Starting from 3 March 2020, we discontinued the use of air-dried slides during breast fine needle aspiration procedures. We selected cases collected during two periods: 2 months before and 2 months after 3 March. In both groups, the number of procedures was recorded together with the distribution of the diagnostic categories and the concordance between cytological and histological results on surgical specimens for lesions suggestive of malignancy, using the chi-squared test. RESULTS: Of the 100 procedures performed during the pre-COVID-19 period, 55% were negative (C2), 3% were non-diagnostic (C1) and 40% were positive (C4 or C5). Of the 75 procedures obtained during the COVID-19 period, 44% were negative (C2), 2.7% were non-diagnostic (C1) and 52% were positive (C4 or C5). Despite the use of a new protocol during the COVID-19 period, we observed concordance between cytological and histological results for lesions suggestive of malignancy. There was no statistically significant difference concerning the distribution of the diagnostic categories in the two groups. CONCLUSIONS: Taking into account the slightly lower number of procedures being analysed during the COVID-19 period, the introduction of a new protocol that does not include air-dried slides is safe and reliable.

Impact of sarcopenia status of muscle-invasive bladder cancer patients on kidney function after neoadjuvant chemotherapy.

BACKGROUND: Sarcopenia is suspected to influence the complication rates in patients undergoing radical cystectomy (RC). The aim of our study was to assess variations in sarcopenia in patients scheduled for neoadjuvant cisplatin-based chemotherapy (NAC) and RC for muscle invasive bladder cancer (MIBC) and to explore the impact of sarcopenia on complications linked to NAC or surgery. METHODS: Between 2012 and 2017, 82 consecutive patients who underwent NAC and RC for cT2-T4 N0 MIBC were retrospectively selected. Using CT scan before and after NAC, Lumbar Skeletal Muscle Index (SMI) was assessed by two observers. We defined severe sarcopenia as SMI <50 cm2/m2 for men and SMI <35 cm2/m2 for women. We evaluated pre- and post-NAC cisplatin-based chemotherapy renal function and post-operative complication rates after cystectomy using the Clavien-Dindo classification. We explored risk factors of complications by logistic regression models. RESULTS: According to the SMI, 47 patients (57.3%) were classified as sarcopenic and 35 patients (42.7%) non-sarcopenic. Patients' characteristics between sarcopenic and non-sarcopenic patients were not significantly different except for BMI (P<0.001). Among patients non-sarcopenic before NAC, nine (25.7%) became sarcopenic after NAC. In multivariate analysis, sarcopenia was an independent significant predictor of renal impairment after NAC (P=0.02). Moreover, sarcopenia and ASA score were independent significant predictors of postoperative early complications (P=0.01 and P=0.03, respectively). CONCLUSIONS: We observed significant changes in sarcopenic status during NAC. Sarcopenia, estimated by the lumbar SMI measurement, was an independent predictor associated with the risk of renal impairment during NAC and early postoperative complications after RC.

Assessment of Fatigue Using Wearable Sensors: A Pilot Study.

BACKGROUND: Fatigue is a broad, multifactorial concept encompassing feelings of reduced physical and mental energy levels. Fatigue strongly impacts patient health-related quality of life across a huge range of conditions, yet, to date, tools available to understand fatigue are severely limited. METHODS: After using a recurrent neural network-based algorithm to impute missing time series data form a multisensor wearable device, we compared supervised and unsupervised machine learning approaches to gain insights on the relationship between self-reported non-pathological fatigue and multimodal sensor data. RESULTS: A total of 27 healthy subjects and 405 recording days were analyzed. Recorded data included continuous multimodal wearable sensor time series on physical activity, vital signs, and other physiological parameters, and daily questionnaires on fatigue. The best results were obtained when using the causal convolutional neural network model for unsupervised representation learning of multivariate sensor data, and random forest as a classifier trained on subject-reported physical fatigue labels (weighted precision of 0.70 ± 0.03 and recall of 0.73 ± 0.03). When using manually engineered features on sensor data to train our random forest (weighted precision of 0.70 ± 0.05 and recall of 0.72 ± 0.01), both physical activity (energy expenditure, activity counts, and steps) and vital signs (heart rate, heart rate variability, and respiratory rate) were important parameters to measure. Furthermore, vital signs contributed the most as top features for predicting mental fatigue compared to physical ones. These results support the idea that fatigue is a highly multimodal concept. Analysis of clusters from sensor data highlighted a digital phenotype indicating the presence of fatigue (95% of observations) characterized by a high intensity of physical activity. Mental fatigue followed similar trends but was less predictable. Potential future directions could focus on anomaly detection assuming longer individual monitoring periods. CONCLUSION: Taken together, these results are the first demonstration that multimodal digital data can be used to inform, quantify, and augment subjectively captured non-pathological fatigue measures.

Automated False Alarm Reduction in a Real-Life Intensive Care Setting Using Motion Detection.

BACKGROUND: Contemporary monitoring systems are sensitive to motion artifacts and cause an excess of false alarms. This results in alarm fatigue and hazardous alarm desensitization. To reduce the number of false alarms, we developed and validated a novel algorithm to classify alarms, based on automatic motion detection in videos. METHODS: We considered alarms generated by the following continuously measured parameters: arterial oxygen saturation, systolic blood pressure, mean blood pressure, heart rate, and mean intracranial pressure. The movements of the patient and in his/her surroundings were monitored by a camera situated at the ceiling. Using the algorithm, alarms were classified into RED (true), ORANGE (possibly false), and GREEN alarms (false, i.e., artifact). Alarms were reclassified by blinded clinicians. The performance was evaluated using confusion matrices. RESULTS: A total of 2349 alarms from 45 patients were reclassified. For RED alarms, sensitivity was high (87.0%) and specificity was low (29.6%) for all parameters. As the sensitivities and specificities for RED and GREEN alarms are interrelated, the opposite was observed for GREEN alarms, i.e., low sensitivity (30.2%) and high specificity (87.2%). As RED alarms should not be missed, even at the expense of false positives, the performance was acceptable. The low sensitivity for GREEN alarms is acceptable, as it is not harmful to tag a GREEN alarm as RED/ORANGE. It still contributes to alarm reduction. However, a 12.8% false-positive rate for GREEN alarms is critical. CONCLUSIONS: The proposed system is a step forward toward alarm reduction; however, implementation of additional layers, such as signal curve analysis, multiple parameter correlation analysis and/or more sophisticated video-based analytics are needed for improvement.

Forecasting intracranial hypertension using multi-scale waveform metrics.

OBJECTIVE: Acute intracranial hypertension is an important risk factor of secondary brain damage after traumatic brain injury. Hypertensive episodes are often diagnosed reactively, leading to late detection and lost time for intervention planning. A pro-active approach that predicts critical events several hours ahead of time could assist in directing attention to patients at risk. APPROACH: We developed a prediction framework that forecasts onsets of acute intracranial hypertension in the next 8 h. It jointly uses cerebral auto-regulation indices, spectral energies and morphological pulse metrics to describe the neurological state of the patient. One-minute base windows were compressed by computing signal metrics, and then stored in a multi-scale history, from which physiological features were derived. MAIN RESULTS: Our model predicted events up to 8 h in advance with an alarm recall rate of 90% at a precision of 30% in the MIMIC-III waveform database, improving upon two baselines from the literature. We found that features derived from high-frequency waveforms substantially improved the prediction performance over simple statistical summaries of low-frequency time series, and each of the three feature classes contributed to the performance gain. The inclusion of long-term history up to 8 h was especially important. SIGNIFICANCE: Our results highlight the importance of information contained in high-frequency waveforms in the neurological intensive care unit. They could motivate future studies on pre-hypertensive patterns and the design of new alarm algorithms for critical events in the injured brain.

Successful Imatinib Treatment of an Abdominal Compartment Syndrome due to Huge Gastrointestinal Stromal Tumour.

Gastrointestinal stromal tumours (GISTs) are the most common digestive mesenchymal tumours, whose prognosis has been revolutionised by targeted therapies such as oral imatinib. Abdomen compartment syndrome (ACS) is associated with mortality superior to 50% in adults. ACS has never been reported to date in patients with GIST. Specific anticancer treatment in critically ill patients in intensive care unit (ICU) remains a matter of debate given the high mortality rate. Here, we report the case of a 58-year-old woman with ACS related to a 40-cm huge GIST and multi-organ failure requiring mechanical ventilation, vasopressive support and haemodialysis. She was treated in emergency with imatinib via the naso-gastric tube (day 1), then at day 3 by decompressive laparotomy and "open abdomen" without any tumour removal. Imaging after 11 days imatinib showed objective tumour response. Because of improvement of multi-organ dysfunctions, the laparotomy was closed at day 14, and the resuscitation procedures were progressively stopped. After discharge from hospital, she survived nearly two years. This is the first case of successful treatment of cancer-associated ACS by targeted therapy and decompressive laparotomy. Imatinib in critically ill patients with GIST may be successful even in presence of multi-organ failure.

Dietary Inclusion of Monosodium Glutamate in Gestating and Lactating Sows Modifies the Preference Thresholds and Sensory-Motivated Intake for Umami and Sweet Solutions in Post-Weaned Pigs.

Pigs show an innate preference for umami (monosodium glutamate, MSG) taste. Nevertheless, the influence of a pre and postnatal umami exposure remains unclear. An experiment was conducted to test the hypothesis that MSG inclusion into maternal diets would modify the feeding behavior of post-weaning pigs. A total of 22 sows were selected on day 85 of gestation and randomly assigned to one of two gestating and lactating programs (standard commercial diets without or with 50 g/kg of MSG). Later, 208 pigs born from these sows were selected to evaluate their preference thresholds, sensory-motivated intake, total consumption, and consumption patterns for MSG and sucrose solutions. Pigs born from MSG-fed sows showed lower (p < 0.045) preference thresholds for MSG and sucrose than did animals born from control sows, and displayed an increased (p < 0.050) sensory-motivated intake for sucrose and decreased for MSG. Conversely, no differences (p > 0.05) were observed in the total consumption or consumption patterns of MSG or sucrose solutions among pigs born from control and MSG-fed sows. It is concluded that the feeding behavior of nursery pigs can be influenced by pre and postnatal inclusion of a taste active compound into maternal diets. It would appear that a compensatory mechanism to balance dietary nutrients might be in place.

Evaluation of 2D and 3D ultrasound tracking algorithms and impact on ultrasound-guided liver radiotherapy margins.

PURPOSE: Compensation for respiratory motion is important during abdominal cancer treatments. In this work we report the results of the 2015 MICCAI Challenge on Liver Ultrasound Tracking and extend the 2D results to relate them to clinical relevance in form of reducing treatment margins and hence sparing healthy tissues, while maintaining full duty cycle. METHODS: We describe methodologies for estimating and temporally predicting respiratory liver motion from continuous ultrasound imaging, used during ultrasound-guided radiation therapy. Furthermore, we investigated the trade-off between tracking accuracy and runtime in combination with temporal prediction strategies and their impact on treatment margins. RESULTS: Based on 2D ultrasound sequences from 39 volunteers, a mean tracking accuracy of 0.9 mm was achieved when combining the results from the 4 challenge submissions (1.2 to 3.3 mm). The two submissions for the 3D sequences from 14 volunteers provided mean accuracies of 1.7 and 1.8 mm. In combination with temporal prediction, using the faster (41 vs 228 ms) but less accurate (1.4 vs 0.9 mm) tracking method resulted in substantially reduced treatment margins (70% vs 39%) in contrast to mid-ventilation margins, as it avoided non-linear temporal prediction by keeping the treatment system latency low (150 vs 400 ms). Acceleration of the best tracking method would improve the margin reduction to 75%. CONCLUSIONS: Liver motion estimation and prediction during free-breathing from 2D ultrasound images can substantially reduce the in-plane motion uncertainty and hence treatment margins. Employing an accurate tracking method while avoiding non-linear temporal prediction would be favorable. This approach has the potential to shorten treatment time compared to breath-hold and gated approaches, and increase treatment efficiency and safety.

Giant Pedunculated Hepatic Hemangioma: A Case Report and Literature Review.

Hepatic hemangioma is the most common benign hepatic tumor, and most of them are small in size and asymptomatic. Giant hepatic hemangiomas are uncommon, but pedunculated giant hemangiomas are even rarer and often difficult to diagnose because of their exophytic development. We report here on a 48-year-old man with a symptomatic pedunculated giant hepatic hemangioma and hepatic angiomatosis, mimicking a gastric gastrointestinal stromal tumor with liver metastases. The preoperative diagnosis was suspected on imaging including CT scan and MRI. The patient was successfully operated (left hepatic lobectomy), without any complication, and the pathological analysis confirmed the diagnosis. We reviewed the English literature, and to our knowledge, our case represents the largest case reported so far when compared with the 19 other informative cases.

Ultrasound-driven 4D MRI.

We present an ultrasound-driven 4D magnetic resonance imaging (US-4DMRI) method for respiratory motion imaging in the thorax and abdomen. The proposed US-4DMRI comes along with a high temporal resolution, and allows for organ motion imaging beyond a single respiratory cycle. With the availability of the US surrogate both inside and outside the MR bore, 4D MR images can be reconstructed for 4D treatment planning and online respiratory motion prediction during radiotherapy. US-4DMRI relies on simultaneously acquired 2D liver US images and abdominal 2D MR multi-slice scans under free respiration. MR volumes are retrospectively composed by grouping the MR slices corresponding to the most similar US images. We present two different US similarity metrics: an intensity-based approach, and a similarity measure relying on predefined fiducials which are being tracked over time. The proposed method is demonstrated on MR liver scans of eight volunteers acquired over a duration of 5.5 min each at a temporal resolution of 2.6 Hz with synchronous US imaging at 14 Hz-17 Hz. Visual inspection of the reconstructed MR volumes revealed satisfactory results in terms of continuity in organ boundaries and blood vessels. In quantitative leave-one-out experiments, both US similarity metrics reach the performance level of state-of-the-art navigator-based approaches.

Acquired Resistance to Tyrosine Kinase Inhibitors in Non-Small Cell Lung Cancers: The Role of Next-Generation Sequencing on Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration Samples.

CONTEXT: - Molecular testing is essential for the diagnostic workup of patients with advanced non-small cell lung cancers. Cytology specimens from minimally invasive procedures, such as endobronchial ultrasound-guided transbronchial needle aspiration, are often the only available samples for these patients. The implementation of molecular diagnostic testing, and in particular next-generation sequencing-based testing, on these cytologic specimens is currently an evolving field for lung cytopathology. The application of these molecular analyses on tyrosine kinase inhibitor-resistant non-small cell lung cancers raises unique technical, biologic, and clinical challenges. OBJECTIVE: - To provide an overview of the implementation of next-generation sequencing analysis on endobronchial ultrasound-guided transbronchial needle aspiration samples to detect the molecular aberrations underneath the phenomenon of acquired resistance in patients with non-small cell lung cancers progressing while on the EGFR/ALK tyrosine kinase inhibitor treatment. DATA SOURCES: - Peer-reviewed original articles, review articles, and published guidelines and expert opinion reports were reviewed, together with our single-center experience. CONCLUSIONS: - Next-generation sequencing analyses and the endobronchial ultrasound-guided transbronchial needle aspiration procedure may represent a valuable strategy to address the unique requirements of molecular testing on tyrosine kinase inhibitor-resistant non-small cell lung cancers.